Abstract
Globally, under-five child mortality is a substantial health problem. In developing countries, reducing child mortality and improving child health are the key priorities in health sectors. Despite the significant reduction in deaths of under-five children globally, developing countries are still struggling to maintain an acceptable mortality rate. Globally, the death rate of under-five children is 41 per 1000 live births. However, the death rate of children in developing nations like Pakistan and Ethiopia per 1000 live births is 74 and 54, respectively. Such nations find it very challenging to decrease the mortality rate. Data analytics on healthcare data plays a pivotal role in identifying the trends and highlighting the key factors behind the children deaths. Similarly, predictive analytics with the help of Internet of Things based frameworks significantly advances the smart healthcare systems to forecast death trends for timely intervention. Moreover, it helps in capturing hidden associations between health-related variables and key death factors among children. In this study, a predictive analytics framework has been developed to predict the death rates with high accuracy and to find the significant determinants that cause high child mortality. Our framework uses an automated method of information gain to rank the information-rich mortality variables for accurate predictions. Ethiopian Demographic Health Survey and Pakistan Demographic Health Survey data sets have been used for the validation of our proposed framework. These real-world data sets have been tested using machine learning classifiers, such as Naïve Bayes, decision tree, rule induction, random forest, and multi-layer perceptron, for the prediction task. It has been revealed through our experimentation that Naïve Bayes classifier predicts the child mortality rate with the highest average accuracy of 96.4% and decision tree helps in identifying key classification rules covering the factors behind children deaths.
Highlights
Child mortality is one of the most widely used measures for the well-being and health of children
It is clear from the low-ranked values of ‘‘place of residence’’ and ‘‘received family planning’’ are less likely to have some relation with the target class
Experiments have been performed on data sets of developing countries, that is, Ethiopia and Pakistan
Summary
Child mortality is one of the most widely used measures for the well-being and health of children. Deaths of millions of under-five children occur, and this death rate could be prevented with timely immunization intervention. Mortality Rate Per 1000 Live Births Years Globally Pakistan. Ethopia still it remains an alarming public health issue for the developing countries. In 2016, the under-five death rate world-wide was 40 deaths per 1000 live births (lb),[1] which was significantly reduced from the previous death rate of 93 per 1000 lb. The desired rate of 25 per 1000 lb by 2030 is still a challenging task for the developing countries.[2]
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